Distributed Learning for Metaverse over Wireless Networks

Metaverse is envisioned to be a human-centric framework that creates an interface for users to immerse themselves in education, professional training, and entertainment by accessing a virtual world. The quality of immersive experiences (QoIE) naturally comes out as a metric to measure the multi-sensory multimedia (MSMM) communication provided by Metaverse networks, we first propose a human-centric MSMM communication framework and highlight the asymmetric uplink-downlink transmission mechanism by identifying their different responsibilities. This MSMM framework raises the need for advanced communication technologies and more computational resources to support the deployment of AI-enabled Metaverse services. Task-oriented communication (TOC), can enhance conventional data-oriented communication by shifting from data rate maximization to task completion communication, especially deep learning-based TOC (DL-TOC) can build up a joint communication and task completion architecture. The idea of investigating distributed computational resources of end users to perform local learning, and only share model parameters with the central server, known as distributed learning framework, becomes popular, which saves communication resources and provides privacy protection. Then, it is introduced as a beneficial scheme to enable training ML models for both Al-enabled services and the DL-TOC scheme in a distributed manner. Specifically, we propose three distributed learning variants to address the heterogeneity of Metaverse networks from different aspects. Next, a case study is proposed to demonstrate how the proposed distributed learning frameworks can assist attention-aware communication for Metaverse. Finally, we identify the challenges and some promising research directions.</p

Longevity risk and survivor derivative pricing

Purpose – Longevity risk, that is, the uncertainty of the demographic survival rate, is an important risk for insurance companies and pension funds, which have large, and long-term, exposures to survivorship. The purpose of this paper is to propose a new model to describe this demographic survival risk. Design/methodology/approach – The model proposed in this paper satisfies all the desired properties of a survival rate and has an explicit distribution for both single years and accumulative years. Findings – The results show that it is important to consider the expected shift and risk premium of life table uncertainty and the stochastic behaviour of survival rates when pricing the survivor derivatives. Originality/value – This model can be applied to the rapidly growing market for survivor derivatives

Principal weighted support vector machines for sufficient dimension reduction in binary classification

© 2017 Biometrika Trust. Sufficient dimension reduction is popular for reducing data dimensionality without stringent model assumptions. However, most existing methods may work poorly for binary classification. For example, sliced inverse regression (Li, 1991) can estimate at most one direction if the response is binary. In this paper we propose principal weighted support vector machines, a unified framework for linear and nonlinear sufficient dimension reduction in binary classification. Its asymptotic properties are studied, and an efficient computing algorithm is proposed. Numerical examples demonstrate its performance in binary classification

Deep Learning Analysis of Urban Growth Boundaries: An Evaluation of Effectiveness in Mitigating Urban Sprawl in China

Although urban growth boundaries (UGBs) have been employed as a planning tool in certain Western cities for decades, they have recently been adopted in Chinese cities to address urban sprawl. However, the effectiveness of UGBs in different types of Chinese cities, particularly those on flatlands versus mountains, has not been studied. This study aimed to compare the efficacy of UGBs in a city on flatlands (Chengdu, China) and a mountainous city (Chongqing, China). We used a deep learning architecture (U-Net) to project urban expansions in 2035 with the presence/absence of UGBs and landscape metrics to evaluate UGBs' effectiveness in mitigating urban sprawl. We found significant differences in historical urban expansion between Chengdu and Chongqing from 1992 to 2019. Chengdu experienced spillover sprawl under a monocentric-dominated urban form, while Chongqing witnessed leapfrog and piece-mall sprawl under a polycentric form. Despite the differences in UGBs designation, the simulations demonstrated that UGBs could mitigate urban sprawl in both cities in 2035, with Chengdu exhibiting more pronounced effectiveness. Notably, UGBs were more effective in controlling spillover sprawl in Chengdu, whereas they could effectively reduce leapfrog sprawl in Chongqing. However, UGBs were constrained by strict top-down land quotas, limiting their potential. These findings suggested that implementing UGBs should adopt differentiated goals and strategies for different types of cities

Comparative non-targeted metabolomic analysis reveals insights into the mechanism of rice yellowing

Yellowing of rice during storage is a highly concerned issue for managing rice quality whereas the yellowing mechanism is not clearly elucidated so far. Thus, the comparative untargeted metabolomic analysis was performed in this study. The results revealed that glycolysis pathway and tricarboxylic acid cycle (TCA) were significantly enhanced in yellowed rice, indicating the activated energy metabolism was trigged during the yellowing process. In addition, the increased aromatic compounds (4-hydroxycinnamic acid and benzoic acid) and their precursors (phenylalanine, tyrosine) suggested the activation of shikimate-phenylpropanoid biosynthesis in yellowed rice, which is an antioxidant defense related pathway. In particular, the pathways involved in the metabolism of glutamate and arginine also significantly altered in yellowed rice. Therefore, the enriched pathways of increased amino acids, sugars, sugar alcohols, and intermediates of the TCA cycle during yellowing process are proposed to be associated with the response of heat and dry induced by the yellowing process. © 2019 Elsevier Lt

Chiral covalent organic frameworks: design, synthesis and property

Covalent organic frameworks (COFs) are constructed using reticular chemistry with the building blocks being connected via covalent bonds and have emerged as a new series of porous materials for multitudinous applications. Most COFs reported to date are achiral, and only a small fraction of COFs with chiral nature are reported. This review covers the recent advances in the field of chiral COFs (CCOFs), including their design principles and synthetic strategies, structural studies, and potential applications in asymmetric catalysis, enantioselective separation, and chiral recognition. Finally, we illustrate the remaining challenges and future opportunities in this field

An Effective Semi-supervised Approach for Liver CT Image Segmentation

Despite the substantial progress made by deep networks in the field of medical image segmentation, they generally require sufficient pixel-level annotated data for training. The scale of training data remains to be the main bottleneck to obtain a better deep segmentation model. Semi-supervised learning is an effective approach that alleviates the dependence on labeled data. However, most existing semi-supervised image segmentation methods usually do not generate high-quality pseudo labels to expand training dataset. In this paper, we propose a deep semi-supervised approach for liver CT image segmentation by expanding pseudo-labeling algorithm under the very low annotated-data paradigm. Specifically, the output features of labeled images from the pretrained network combine with corresponding pixel-level annotations to produce class representations according to the mean operation. Then pseudo labels of unlabeled images are generated by calculating the distances between unlabeled feature vectors and each class representation. To further improve the quality of pseudo labels, we adopt a series of operations to optimize pseudo labels. A more accurate segmentation network is obtained by expanding the training dataset and adjusting the contributions between supervised and unsupervised loss. Besides, the novel random patch based on prior locations is introduced for unlabeled images in the training procedure. Extensive experiments show our method has achieved more competitive results compared with other semi-supervised methods when fewer labeled slices of LiTS dataset are available

Polymorphisms and their Haplotype Combinations in the Lysozyme Gene Associated with the Production Traits of a Chinese Native Chicken Breed

<div><p>ABSTRACT Animal lysozymes, which have been studied in many of invertebrate and vertebrate species, have been characterized and demonstrated to be immune-associated molecules, digestive enzymes and multifunctional molecules. The purpose of this study was to detect the connection between lysozyme-gene polymorphism and the production traits of a Chinese native chicken breed (Langshan chicken). Four single nucleotide mutation sites were identified: G345A, C1726T, G1836A, A1838G. By the linkage disequilibrium analysis, six haplotypes and 15haplotype combinations were depicted in the studied population. The statistical analysis demonstrated that the SNPs and the haplotype combinations are related to body weight at sixteen weeks of age in Langshan chickens (p<0.05), and those with combined haplotype Hap3-Hap6 (GA-TT-GG-AA) presented higher body weight. Our study demonstrated that the SNPs and their haplotype combinations in the lysozyme gene were associated with the chicken production traits, and that SNPs can be used as a molecular marker for chicken marker-assisted selection.</p></div

Tropical methane emissions explain large fraction of recent changes in global atmospheric methane growth rate

Large variations in the growth of atmospheric methane, a prominent greenhouse gas, are driven by a diverse range of anthropogenic and natural emissions and by loss from oxidation by the hydroxyl radical. We used a decade-long dataset (2010–2019) of satellite observations of methane to show that tropical terrestrial emissions explain more than 80% of the observed changes in the global atmospheric methane growth rate over this period. Using correlative meteorological analyses, we show strong seasonal correlations (r = 0.6–0.8) between large-scale changes in sea surface temperature over the tropical oceans and regional variations in methane emissions (via changes in rainfall and temperature) over tropical South America and tropical Africa. Existing predictive skill for sea surface temperature variations could therefore be used to help forecast variations in global atmospheric methane

Effects of End-Caps on the Atropisomerization, Polymerization, and the Thermal Properties of ortho-Imide Functional Benzoxazines.

A new type of atropisomerism has recently been discovered in 1,3-benzoxazines, where the intramolecular repulsion between negatively charged oxygen atoms on the imide and the oxazine ring hinders the rotation about the C⁻N bond. The imide group offers a high degree of flexibility for functionalization, allowing a variety of functional groups to be attached, and producing different types of end-caps. In this work, the effects of end-caps on the atropisomerism, thermally activated polymerization of ortho-imide functional benzoxazines, and the associated properties of polybenzoxazines have been systematically investigated. Several end-caps, with different electronic characteristics and rigidities, were designed. ¹H and 13C nuclear magnetic resonance (NMR) spectroscopy and density functional theory (DFT) calculations were employed to obtain structural information, and differential scanning calorimetry (DSC) and in situ Fourier transform infrared (FT-IR) spectroscopy were also performed to study the thermally activated polymerization process of benzoxazine monomers. We demonstrated that the atropisomerization can be switched on/off by the manipulation of the steric structure of the end-caps, and polymerization behaviors can be well-controlled by the electronic properties of the end-caps. Moreover, a trade-off effect were found between the thermal properties and the rigidity of the end-caps in polybenzoxazines